AIMC Topic: Algorithms

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Interpretable graph Kolmogorov-Arnold networks for multi-cancer classification and biomarker identification using multi-omics data.

Scientific reports
The integration of heterogeneous multi-omics datasets at a systems level remains a central challenge for developing analytical and computational models in precision cancer diagnostics. This paper introduces Multi-Omics Graph Kolmogorov-Arnold Network...

IoT enabled health monitoring system using rider optimization algorithm and joint process estimation.

Scientific reports
The timely detection of abnormal health conditions is crucial in achieving successful medical intervention and enhancing patient outcomes. Despite advances in health monitoring, existing methods often struggle with achieving high accuracy, sensitivit...

The potential of machine learning in classifying relapse and non-relapse in children with clubfoot based on movement patterns.

Scientific reports
The diverse nature and timing of a clubfoot relapse pose challenges for early detection. A relapsed clubfoot typically involves a combination of deformities affecting a child's movement pattern across multiple joint levels, formed by a complex kinema...

Classification of skin diseases with deep learning based approaches.

Scientific reports
Skin diseases are one of the most common health problems that affect people of all ages around the world and significantly reduce the quality of life of individuals. Diseases of eczema, seborrheic dermatitis and skin cancer need to be diagnosed and c...

A new low-rank adaptation method for brain structure and metastasis segmentation via decoupled principal weight direction and magnitude.

Scientific reports
Deep learning techniques have become pivotal in medical image segmentation, but their success often relies on large, manually annotated datasets, which are expensive and labor-intensive to obtain. Additionally, different segmentation tasks frequently...

Enhancing surface electromyographic signal recognition accuracy for trans-radial amputees using broad learning systems.

Biomedical physics & engineering express
Gesture recognition based on surface electromyography (sEMG) plays a crucial role in human-computer interaction. By analyzing sEMG signals generated from residual forearm muscle activity in trans-radial amputees, it is possible to predict their hand ...

Multi-modal classification of retinal disease based on convolutional neural network.

Biomedical physics & engineering express
Retinal diseases such as age-related macular degeneration and diabetic retinopathy will lead to irreversible blindness without timely diagnosis and treatment. Optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) imag...

Hyperparameter tuned deep learning-driven medical image analysis for intracranial hemorrhage detection.

PloS one
Intracranial haemorrhage (ICH) is a crucial medical emergency that entails prompt assessment and management. Compared to conventional clinical tests, the need for computerized medical assistance for properly recognizing brain haemorrhage from compute...

AI-driven skin cancer detection from smartphone images: A hybrid model using ViT, adaptive thresholding, black-hat transformation, and XGBoost.

PloS one
Skin cancer is a significant global public health issue, with millions of new cases identified each year. Recent breakthroughs in artificial intelligence, especially deep learning, possess considerable potential to enhance the accuracy and efficiency...